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10.1371/journal.pone.0186353 http://scihub22266oqcxt.onion/10.1371/journal.pone.0186353 C5673205!5673205 !29108005     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=29108005 &cmd=llinks): Failed to open stream: HTTP request failed! 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Identification of genes and critical control proteins associated with inflammatory breast cancer using network controllability |pdf=|usr=}}{{29108005 }} gab.com Text Identification of genes and critical control proteins associated with inflammatory breast cancer using network controllability JO: PLoS One http://www.kidney.de/pget.php?&tw=1&pmid=29108005 #FOAvip One of the most aggressive forms of breast cancer is inflammatory breast cancer (IBC), whose lack of tumour mass also makes a prompt diagnosis difficult. Moreover, genomic differences between common breast cancers and IBC have not been completely assessed, thus substantially limiting the identification of biomarkers unique to IBC. Here, we developed a novel statistical analysis of gene expression profiles corresponding to microdissected IBC, non-IBC (nIBC) and normal samples that enabled us to identify a set of genes significantly associated with a specific disease state. Second, by using advanced methods based on controllability network theory, we identified a set of critical control proteins that uniquely and structurally control the entire proteome. By mapping high change variance genes in protein interaction networks, we found that a large statistically significant fraction of genes whose variance changed significantly between normal and IBC and nIBC disease states were among the set of critical control proteins. Moreover, this analysis identified the overlapping genes with the highest statistical significance; these genes may assist in developing future biomarkers and determining drug targets to disrupt the molecular pathways driving carcinogenesis in IBC. Twit Text FOAVip Identification of genes and critical control proteins associated with inflammatory breast cancer using network controllability ????PLoS One http://www.kidney.de/pget.php?&tw=1&pmid=29108005 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=29108005 #FOAvip English Wikipedia <ref>{{Cite pmid|29108005 }}</ref> Identification of genes and critical control proteins associated with inflammatory breast cancer using network controllability #MMPMID29108005 Wakai R ; Ishitsuka M ; Kishimoto T ; Ochiai T ; Nacher JC PLoS One 2017[]; 12 (11 ): e0186353 PMID29108005 show ga One of the most aggressive forms of breast cancer is inflammatory breast cancer (IBC), whose lack of tumour mass also makes a prompt diagnosis difficult. Moreover, genomic differences between common breast cancers and IBC have not been completely assessed, thus substantially limiting the identification of biomarkers unique to IBC. Here, we developed a novel statistical analysis of gene expression profiles corresponding to microdissected IBC, non-IBC (nIBC) and normal samples that enabled us to identify a set of genes significantly associated with a specific disease state. Second, by using advanced methods based on controllability network theory, we identified a set of critical control proteins that uniquely and structurally control the entire proteome. By mapping high change variance genes in protein interaction networks, we found that a large statistically significant fraction of genes whose variance changed significantly between normal and IBC and nIBC disease states were among the set of critical control proteins. Moreover, this analysis identified the overlapping genes with the highest statistical significance; these genes may assist in developing future biomarkers and determining drug targets to disrupt the molecular pathways driving carcinogenesis in IBC. |*Gene Expression Profiling [MESH] |*Gene Regulatory Networks [MESH] |*Protein Interaction Maps [MESH] |Female [MESH] |Humans [MESH]Identification of genes and critical control proteins associated with (epmc).pdf DeepDyve Pubget Overpricing